A real-world pharmacovigilance study of four anti-non-small cell lung cancer drugs using the WHO-VigiAccess database

Chunyue Fang1,2, Junzhu Wu1, Chouqi Hu1,2

  • 1College of Pharmacy, Dali University, Dali, Yunnan, China.

Medicine
|May 23, 2026
PubMed

Insights

This study analyzed real-world adverse drug reactions for anlotinib, gefitinib, afatinib, and osimertinib in non-small cell lung cancer. Findings reveal common and unique safety profiles, aiding personalized treatment strategies.

Area of Science:

  • Pharmacovigilance
  • Oncology
  • Real-world evidence

Background:

  • Established efficacy of anlotinib, gefitinib, afatinib, and osimertinib in non-small cell lung cancer (NSCLC).
  • Gaps exist in the comprehensive safety evidence for these NSCLC treatments.
  • Need for real-world data to understand post-marketing adverse drug reactions (ADRs).

Purpose of the Study:

  • To evaluate post-marketing ADRs of anlotinib, gefitinib, afatinib, and osimertinib using real-world data.
  • To identify and analyze potential ADR signals for these four NSCLC drugs.
  • To compare the safety profiles and inform personalized treatment approaches.

Main Methods:

  • Utilized World Health Organization-VigiAccess database for ADR data up to April 30, 2025.
  • Employed statistical methods including reporting odds ratio, proportional reporting ratio, multi-item gamma Poisson shrinker, and Bayesian confidence propagation neural network.
  • Analyzed 52,978 adverse event reports: 1642 for anlotinib, 10,294 for gefitinib, 12,493 for afatinib, and 28,549 for osimertinib.

Main Results:

  • All four drugs are associated with skin/subcutaneous tissue and gastrointestinal disorders.
  • Specific ADR profiles and signal intensities vary among the four medications.
  • Identified commonalities and unique ADRs, largely consistent with drug labels but with notable differences.

Conclusions:

  • Anlotinib, gefitinib, afatinib, and osimertinib exhibit shared and distinct ADR profiles in NSCLC treatment.
  • Real-world data analysis reveals safety signals that complement drug label information.
  • Findings support personalized medication strategies based on drug-specific characteristics and patient conditions.

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